Adobe, Inc.

Oliver Markus Michael Brdiczka

Aliakbar Darabi

Doo Soon Kim

Nipun Jindal

Peter Evan O'Donovan

Yinglan Ma

Razvan Cotlarciuc

Ripul Bhutani

Siddartha Reddy Turpu

Costin-Stefan Ion

Font recommendation techniques are described that provide recommendations of fonts based on a variety of factors, automatically and without user intervention in real time. This is performable in a variety of ways by addressing a wide range of considerations as part of machine learning, examples of which include context, popularity, similarity, customization, and topic compatibility.

Font recommendation

In implementations of systems for generating suggestions with knowledge graph embedding vectors, a computing device implements a suggestion system to receive input data describing user interactions with an application for editing digital content. The suggestion system generates input embedding vectors based on the user interactions with the application and determines an item based on the input embedding vectors and knowledge graph embedding vectors generated from nodes of a knowledge graph describing a tutorial for editing digital content. The suggestion system generates an indication of the item for display in a user interface of a display device.

Systems for generating suggestions with knowledge graph embedding vectors

Growing community of inventors

San Jose, CA, United States of America

Oliver Markus Michael Brdiczka